John A.W. McCall
researcher
Facts
7 properties- Instance of
- human
- Occupation
- researcher
- Employer
- School of Computing[2]
- Imported from
- wholeness_audit_2026-05-02
🏷️ Also known as
en John A.W. McCall
🔖 Identifiers · 10
- ORCID iD
- 0000-0003-1738-7056
- VIAF cluster ID
- 312607900
- GND ID
- 1048598020
- OpenAlex ID
- A5027645309as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- DBLP author ID
- 00/484
- Google Scholar author ID
- cBFoTs0AAAAJ
- IxTheo authority ID
- 780695895
- ResearcherID
- G-1423-2011
- Scopus author ID
- 36797474900
- WorldCat Entities ID
- E39PBJrcqmFxF4wfy3qy9DKmVC
📚 Sources · 1
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 14
A comparative study of anomaly detection methods for gross error detection problems,
Ensemble of deep learning models with surrogate-based optimization for medical image segmentation,
Ensemble Selection based on Classifier Prediction Confidence,
Estimation of distribution algorithms for the Multi-Mode Resource Constrained Project scheduling problem,
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems,
Evolving interval-based representation for multiple classifier fusion,
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems,
Limitations of benchmark sets and landscape features for algorithm selection and performance prediction
+6 more
← Authored by 14
A comparative study of anomaly detection methods for gross error detection problems,
Ensemble of deep learning models with surrogate-based optimization for medical image segmentation,
Ensemble Selection based on Classifier Prediction Confidence,
Estimation of distribution algorithms for the Multi-Mode Resource Constrained Project scheduling problem,
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems,
Evolving interval-based representation for multiple classifier fusion,
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems,
Limitations of benchmark sets and landscape features for algorithm selection and performance prediction
+6 more
Affiliated with 1
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